Recent and continuous advancements in neuroengineering and Machine Learning demonstrates the huge potential of Brain-machine interface in the field of neuroprosthetics. This rapidly evolving technology aims to provide innovative solutions to people affected by disabilities, in order to restore motor, sensory and cognitive functions. This is the goal of B-Cratos project, whose purpose is the development of a closed-loop neural interface for controlling a robotic hand prosthesis also capable of providing sensory feedback to the patient. Neural decoding is possible thanks to Deep Learning models trained using high-performance computing resources on datasets acquired from the German Primate Center (Deutsches Primatenzentrum, DPZ), that can classify signals recorded via implanted microelectrode arrays.